This video is part of the Machine Intelligence in Autonomous Vehicles Summit, Amsterdam, 2017 Event. If you would like to access all of the videos please click here.

PANEL: How Can We Apply ML & DL to Accelerate The Autonomous Vehicle?

Questions explored include:
What are the most important areas of deep learning for autonomous vehicles?
What are the key trends in perception for autonomous vehicles?
How should researchers and the automotive industry work together to progress autonomous vehicles?
How should advances in deep learning work with autonomous vehicles regulation?
What are the main non-technology barriers to autonomous vehicles?

Indra is an experienced deep learning engineer and mentor. He is the founder of 23insights, a machine learning startup building solutions that transform the world’s most important industries by applying state-of-the art AI techniques. For Udacity, he mentors students pursuing a Self-Driving Car Nanodegree and he is also responsible for reviewing student projects in Deep Learning. Indra has a background in Computational Intelligence and he worked several years as Data Scientist for IPG Mediabrands and Screen6 before founding 23insights.

Pejvan Beigui, CTO at EasyMile

Prior to moving to London and join one of the largest hedge-funds as their CTO, Pejvan worked for Apple an evangelist in the Worldwide Developer Relations team. Pejvan was subsequently VP of technology of top-tier investment banks (JPMorgan, MorganStanley, BarCap) where he built trading systems for vanilla and exotic derivatives on commodities. After 10 years spent between London and Singapore, Pejvan returned to France as the CTO for Mozoo, a startup building innovative formats for the mobile web. He joined the early stage start-up EasyMile in 2014 as their CTO. In his spare time, he enjoys coding, photography and writing about himself in the third person.

Jim Aldon D'Souza, Research Engineer at TomTom

Jim is a research engineer working with autonomous driving systems at TomTom. His primary interests lie in the perception, localization, and mapping aspects of self-driving technology. He has a master's in electrical engineering from the Technical University of Denmark, and a bachelor's from National Institute of Technology Karnataka, India. His master's thesis addresses the localization issues faced by a planetary rover when navigating in a symmetrical and featureless environment such as the one on the surface of Mars. It was concluded in 2016 at the German Research Center for Artificial Intelligence in Bremen, Germany.